Convolutional neural networks (CNNs) have achieved superior performance but still lack clarity about the nature and properties of feature extraction. In this paper, by analyzing the sensitivity of neural networks to frequencies and scales, we find that neural networks not only have low- and mediumfrequency biases but also prefer different frequency bands for different classes, and the scale of objects influences the preferred frequency bands. These observations lead to the hypothesis that neural networks must learn the ability to extract features at various scales and frequencies. To corroborate this hypothesis, we propose a network architecture based on Gaussian derivatives, which extracts features by constructing scale space and employing partial derivatives as local feature extraction operators to separate high-frequency information. This manually designed method of extracting features from different scales allows our GSSDNets to achieve comparable accuracy with vanilla networks on various datasets.
Abstract Stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), is one of the most devastating diseases of wheat worldwide. Identifying resistance genes is crucial for developing resistant cultivars to control the disease. Spring wheat PI 660072 (Triticum aestivum) has been identified to possess both adult-plant resistance (APR) and all-stage resistance (ASR) to stripe rust. To elucidate the genetic basis of the resistance in PI 660072, a mapping population consisting of 211 F5 - F7 recombinant inbred lines (RILs) was developed from a cross of PI 660072 with susceptible spring wheat Avocet S. The mapping population was phenotyped for stripe rust responses across five field environments from 2020 to 2022 and genotyped using the 15K SNP (single nucleotide polymorphism) array to map stripe rust resistance loci. The mapping population was also tested at the seedling stage with predominant Chinese Pst races CYR31, CYR32, CYR34 and PST-YX1-3-1 in the greenhouse. Stripe rust resistance genes were identified using the quantitative trait locus (QTL) mapping approach. Two QTL were identified with QYrPI660072.swust-2BL mapped on the long arm of chromosome 2B for ASR and QYrPI660072.swust-4BL on the long arm of chromosome 4B for APR. To facilitate marker-assisted selection breeding, Kompetitive allele specific PCR (KASP) markers, KASP-1269 for QYrPI660072.swust-2BL and KASP-3209 for QYrPI660072.swust-4BL, were developed. These markers could be used to introgress the effective resistance QTL into new wheat cultivars.
In this paper, we present a pressure-oscillation-free projection algorithm for two-phase flows on collocated grids based on the incremental pressure correction algorithm. Particularly, we extend the momentum-weighted interpolation (MWI) scheme to the phase-field method to effectively suppress the unphysical pressure oscillation in solutions of the two-phase flows. Furthermore, the consistent and conservative mass flux has been introduced to conserve mass and momentum transfer in the interfacial flow system. The Navier-Stokes and Cahn-Hilliard equations are both solved within the finite volume method framework, and the convection terms involved are discretized with the weighted essentially non-oscillating (WENO) scheme consistently. The proposed numerical scheme is further verified through numerical experiments.
Perilla frutescens is a widely used medicinal and edible plant with a rich chemical composition throughout its whole plant. The Chinese Pharmacopoeia categorizes P. frutescens leaves(Perillae Folium), seeds(Perillae Fructus), and stems(Perillae Caulis) as three distinct medicinal parts due to the differences in types and content of active components. Over 350 different bioactive compounds have been reported so far, including volatile oils, flavonoids, phenolic acids, triterpenes, sterols, and fatty acids. Due to the complexity of its chemical composition, P. frutescens exhibits diverse pharmacological effects, including antibacterial, anti-inflammatory, anti-allergic, antidepressant, and antitumor activities. While scholars have conducted a substantial amount of research on different parts of P. frutescens, including analysis of their chemical components and pharmacological mechanisms of action, there has yet to be a systematic comparison and summary of chemical components, pharmacological effects, and mechanisms of action. Therefore, this study overviewed the chemical composition and structures of Perillae Folium, Perillae Fructus, and Perillae Caulis, and summarized the pharmacological effects and mechanisms of P. frutescens to provide a reference for better development and utilization of this valuable plant.
Abstract In order to improve compactness of asphalt mixture, a novel vacuum compaction method is proposed and its process parameters are optimized. A simple compaction cylinder with a hole adjusting air pressure was designed and fabricated based on marshal compaction cylinder design. Common compaction and vacuum compaction were conducted separately by using compaction cylinder. The experimental results demonstrate that accumulative compaction depth with vacuum compaction was deeper compared to that of common compaction in the same compaction repetitions. In vacuum compaction, the effect of compaction at -0.08 Mpa presented the best performance. Accumulative compaction depth at - 0.08 Mpa is 3.41mm deeper than that in common compaction, increased 20.53%. Meanwhile, density, porosity, voids in mineral aggregate and percentage of asphalt volume also exhibits that vacuum degree of -0.08 Mpa is most efficient pressure value. These results indicate that vacuum compaction method can effectively improve compactness of asphalt mixture, which could provide a novel method for the enhancement of road quality and road lifespan.
Introduction Agronomic traits are key components of wheat yield. Exploitation of the major underlying quantitative trait loci (QTLs) can improve the yield potential in wheat breeding. Methods In this study, we constructed a recombinant inbred line (RIL) population from Mingxian 169 (MX169) and Pindong 34 (PD34) to determine the QTLs for grain length (GL), grain width (GW), grain length-to-width ratio (LWR), plant height (PH), spike length (SL), grain number per spike (GNS), and the thousand grain weight (TGW) across four environments using wheat 90K SNP array. Results A QTL associated with TGW, i.e., QTGWpd.swust-6BS , was identified on chromosome 6B, which explained approximately 14.1%–16.2% of the phenotypic variation. In addition, eight QTLs associated with GL were detected across six chromosomes in four different test environments. These were QGLpd.swust-1BL , QGLpd.swust-2BL , QGLpd.swust-3BL.1 , QGLpd.swust-3BL.2 , QGLpd.swust-5DL , QGLpd.swust-6AL , QGLpd.swust-6DL.1 , and QGLpd.swust-6DL.2 . They accounted for 9.0%–21.3% of the phenotypic variation. Two QTLs, namely, QGWpd.swust-3BS and QGWpd.swust-6DL , were detected for GW on chromosomes 3B and 6D, respectively. These QTLs explained 12.8%–14.6% and 10.8%–15.2% of the phenotypic variation, respectively. In addition, two QTLs, i.e., QLWRpd.swust-7AS.1 and QLWRpd.swust-7AS.2 , were detected on chromosome 7A for the grain LWR, which explained 10.9%–11.6% and 11.6%–11.2% of the phenotypic variation, respectively. Another QTL, named QGNSpd-swust-6DS , was discovered on chromosome 6D, which determines the GNS and which accounted for 11.4%–13.8% of the phenotypic variation. Furthermore, five QTLs associated with PH were mapped on chromosomes 2D, 3A, 5A, 6B, and 7B. These QTLs were QPHpd.swust-2DL , QPHpd.swust-3AL , QPHpd.swust-5AL , QPHpd.swust-6BL , and QPHpd.swust-7BS , which accounted for 11.3%–19.3% of the phenotypic variation. Lastly, a QTL named QSLpd.swust-3AL , conferring SL, was detected on chromosome 3A and explained 16.1%–17.6% of the phenotypic variation. All of these QTLs were defined within the physical interval of the Chinese spring reference genome. Discussion The findings of this study have significant implications for the development of fine genetic maps, for genomic breeding, and for marker-assisted selection to enhance wheat grain yield.
Aurantii Fructus Immaturus and Aurantii Fructus are the dried young and immature fruits of Rutaceae, which mainly originate from the same part of lime. They are harvested from the same part with different maturity levels, which leads to different medicinal materials. It has been reported that Aurantii Fructus Immaturus and Aurantii Fructus contain flavonoids, alkaloids, volatile oils, coumarins and other components, which have a variety of pharmacological effects such as gastrointestinal disorder-alleviating, anti-anxiety, lipid metabolism-modulating, anti-inflammatory, antimicrobial, and antioxidant effects. This paper reviews the research progress in the evolution, chemical constituents, pharmacological effects, and quality control of Aurantii Fructus Immaturus and Aurantii Fructus, aiming to provide a basis for the quality control and diversified application of the two herbal medicines.
'/%3e%3cuse xlink:href='%23a' transform='rotate(23.036 .093 25.536)'/%3e%3cuse xlink:href='%23a' transform='rotate(45.87 1.273 16.18)'/%3e%3cuse xlink:href='%23a' transform='rotate(69.945 .996 12.078)'/%3e%3cuse xlink:href='%23a' transform='rotate(20.66 -19.689 31.932)'/%3e%3c/svg%3e)
'/%3e%3cuse xlink:href='%23a' transform='translate(288.889 -214.211)'/%3e%3cuse xlink:href='%23a' transform='translate(108 342.749)'/%3e%3cuse xlink:href='%23a' transform='translate(469.189 342.749)'/%3e%3c/svg%3e)